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Journal articleGolahmadi AK, Khan DZ, Mylonas GP, et al., 2021,
Tool-tissue forces in surgery: A systematic review
, Annals of Medicine and Surgery, Vol: 65, Pages: 1-7, ISSN: 2049-0801BackgroundExcessive tool-tissue interaction forces often result in tissue damage and intraoperative complications, while insufficient forces prevent the completion of the task. This review sought to explore the tool-tissue interaction forces exerted by instruments during surgery across different specialities, tissues, manoeuvres and experience levels.Materials & methodsA PRISMA-guided systematic review was carried out using Embase, Medline and Web of Science databases.ResultsOf 462 articles screened, 45 studies discussing surgical tool-tissue forces were included. The studies were categorized into 9 different specialities with the mean of average forces lowest for ophthalmology (0.04N) and highest for orthopaedic surgery (210N). Nervous tissue required the least amount of force to manipulate (mean of average: 0.4N), whilst connective tissue (including bone) required the most (mean of average: 45.8). For manoeuvres, drilling recorded the highest forces (mean of average: 14N), whilst sharp dissection recorded the lowest (mean of average: 0.03N). When comparing differences in the mean of average forces between groups, novices exerted 22.7% more force than experts, and presence of a feedback mechanism (e.g. audio) reduced exerted forces by 47.9%.ConclusionsThe measurement of tool-tissue forces is a novel but rapidly expanding field. The range of forces applied varies according to surgical speciality, tissue, manoeuvre, operator experience and feedback provided. Knowledge of the safe range of surgical forces will improve surgical safety whilst maintaining effectiveness. Measuring forces during surgery may provide an objective metric for training and assessment. Development of smart instruments, robotics and integrated feedback systems will facilitate this.
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Journal articleEspinosa-Gonzalez AB, Neves AL, Fiorentino F, et al., 2021,
Predicting Risk of Hospital Admission in Patients With Suspected COVID-19 in a Community Setting: Protocol for Development and Validation of a Multivariate Risk Prediction Tool
, JMIR RESEARCH PROTOCOLS, Vol: 10, ISSN: 1929-0748- Author Web Link
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- Citations: 8
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Journal articleDryden SD, Anastasova S, Satta G, et al., 2021,
Rapid uropathogen identification using surface enhanced Raman spectroscopy active filters.
, Scientific Reports, Vol: 11, Pages: 1-10, ISSN: 2045-2322Urinary tract infection is one of the most common bacterial infections leading to increased morbidity, mortality and societal costs. Current diagnostics exacerbate this problem due to an inability to provide timely pathogen identification. Surface enhanced Raman spectroscopy (SERS) has the potential to overcome these issues by providing immediate bacterial classification. To date, achieving accurate classification has required technically complicated processes to capture pathogens, which has precluded the integration of SERS into rapid diagnostics. This work demonstrates that gold-coated membrane filters capture and aggregate bacteria, separating them from urine, while also providing Raman signal enhancement. An optimal gold coating thickness of 50 nm was demonstrated, and the diagnostic performance of the SERS-active filters was assessed using phantom urine infection samples at clinically relevant concentrations (105 CFU/ml). Infected and uninfected (control) samples were identified with an accuracy of 91.1%. Amongst infected samples only, classification of three bacteria (Escherichia coli, Enterococcus faecalis, Klebsiella pneumoniae) was achieved at a rate of 91.6%.
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Journal articleKedrzycki M, Leiloglou M, Leff D, et al., 2021,
Versatility in fluorescence guided surgery with the GLOW camera system
, Surgical Life: The Journal of the Association of Surgeons of Great Britain and Ireland, Vol: 59 -
Journal articleSivan M, Rayner C, Delaney B, 2021,
Fresh evidence of the scale and scope of long covid
, BMJ-BRITISH MEDICAL JOURNAL, Vol: 373, ISSN: 0959-535X- Author Web Link
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- Citations: 34
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Journal articleEspinosa-Gonzalez AB, Neves AL, Fiorentino F, et al., 2021,
Predicting Risk of Hospital Admission in Patients With Suspected COVID-19 in a Community Setting: Protocol for Development and Validation of a Multivariate Risk Prediction Tool (Preprint)
<sec> <title>BACKGROUND</title> <p>During the pandemic, remote consultations have become the norm for assessing patients with signs and symptoms of COVID-19 to decrease the risk of transmission. This has intensified the clinical uncertainty already experienced by primary care clinicians when assessing patients with suspected COVID-19 and has prompted the use of risk prediction scores, such as the National Early Warning Score (NEWS2), to assess severity and guide treatment. However, the risk prediction tools available have not been validated in a community setting and are not designed to capture the idiosyncrasies of COVID-19 infection.</p> </sec> <sec> <title>OBJECTIVE</title> <p>The objective of this study is to produce a multivariate risk prediction tool, RECAP-V1 (Remote COVID-19 Assessment in Primary Care), to support primary care clinicians in the identification of those patients with COVID-19 that are at higher risk of deterioration and facilitate the early escalation of their treatment with the aim of improving patient outcomes.</p> </sec> <sec> <title>METHODS</title> <p>The study follows a prospective cohort observational design, whereby patients presenting in primary care with signs and symptoms suggestive of COVID-19 will be followed and their data linked to hospital outcomes (hospital admission and death). Data collection will be carried out by primary care clinicians in four arms: North West London Clinical Commissioning Groups (NWL CCGs), Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), Covid Clinical Assessment Service (CCAS), and South East London CCGs (Doctaly platform). The study involves the use o
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Journal articleSounderajah V, Clarke J, Yalamanchili S, et al., 2021,
A national survey assessing public readiness for digital health strategies against COVID-19 within the United Kingdom
, Scientific Reports, Vol: 11, Pages: 1-24, ISSN: 2045-2322There is concern that digital public health initiatives used in the management of COVID-19 may marginalise certain population groups. There is an overlap between the demographics of groups at risk of digital exclusion (older, lower social grade, low educational attainment and ethnic minorities) and those who are vulnerable to poorer health outcomes from SARS-CoV-2. In this national survey study (n=2040), we assessed how the UK population; particularly these overlapping groups, reported their preparedness for digital health strategies. We report, with respect to using digital information to make health decisions, that those over 60 are less comfortable (net comfort: 57%) than those between 18-39 (net comfort: 78%) and lower social grades are less comfortable (net comfort: 63%) than higher social grades (net comfort: 75%). With respect to a preference for digital over non-digital sources in seeking COVID-19 health information, those over 60 (net preference: 21%) are less inclined than those between 18-39 (net preference: 60%) and those of low educational attainment (net preference: 30%) are less inclined than those of high educational attainment (net preference: 52%). Lastly, with respect to distinguishing reliable digital COVID-19 information, lower social grades (net confidence: 55%) are less confident than higher social grades (net confidence: 68%) and those of low educational attainment (net confidence: 51%) are less confident than those of high educational attainment (net confidence: 71%). All reported differences are statistically significant (p<0.01) following multivariate regression modelling. This study suggests that digital public health approaches to COVID-19 have the potential to marginalise groups who are concurrently at risk of digital exclusion and poor health outcomes from SARS-CoV-2.
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Journal articleKostopoulou O, Tracey C, Delaney B, 2021,
Can decision support combat incompleteness and bias in routine primary care data?
, Journal of the American Medical Informatics Association, ISSN: 1067-5027Objective: Routine primary care data may be used for the derivation of clinical prediction rules and risk scores. We sought to measure the impact of a decision support system (DSS) on data completeness and freedom from bias.Materials and Methods: We used the clinical documentation of 34 UK general practitioners who took part in a previous study evaluating the DSS. They consulted with 12 standardized patients. In addition to suggesting di- agnoses, the DSS facilitates data coding. We compared the documentation from consultations with the elec- tronic health record (EHR) (baseline consultations) vs consultations with the EHR-integrated DSS (supported consultations). We measured the proportion of EHR data items related to the physician’s final diagnosis. We expected that in baseline consultations, physicians would document only or predominantly observations re- lated to their diagnosis, while in supported consultations, they would also document other observations as a re- sult of exploring more diagnoses and/or ease of coding.Results: Supported documentation contained significantly more codes (incidence rate ratio [IRR] 1⁄4 5.76 [4.31, 7.70] P < .001) and less free text (IRR 1⁄4 0.32 [0.27, 0.40] P < .001) than baseline documentation. As expected, the proportion of diagnosis-related data was significantly lower (b 1⁄4 0.08 [0.11, 0.05] P < .001) in the supported consultations, and this was the case for both codes and free text.Conclusions: We provide evidence that data entry in the EHR is incomplete and reflects physicians’ cognitive biases. This has serious implications for epidemiological research that uses routine data. A DSS that facilitates and motivates data entry during the consultation can improve routine documentation.
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Journal articlevan Dael J, Neves AL, Painter A, et al., 2021,
Patient perspectives on the use of digital health services at a multi-site hospital in North-West London: a quantitative content analysis (Preprint)
, Journal of Medical Internet Research, ISSN: 1438-8871Background:Following a large increase in the adoption of digital health amidst the COVID-19 crisis, there is increasing policy interest in the longer-term implementation of digital health services. Yet, there is still much unknown about the inherent quality of remote digital care, and research on patient perspectives remains comparatively small. Widespread usage amidst COVID-19 presents an important opportunity to better understand patients’ first-hand experiences with using these technologies.Objective:This study examined patients’ perspectives on main benefits and concerns with using digital health services in a large multi-site teaching hospital in North-West London during the COVID-19 crisis.Methods:Qualitative data was obtained from a larger questionnaire conducted during the COVID-19 pandemic on Care Information Exchange, which represents the largest patient-facing electronic health records in the English National Health Service. All responses were analysed using the framework analysis method. Quantitative content analysis was performed by mapping frequencies of reported themes across the respondent population.Results:Of all 6,766 respondents, 25.1% reported to have no concerns with digital health services, compared to 3.0% reporting no benefits. Reported benefits included: ease of access (37.1%), feeling empowered and informed (23.2%), improved timeliness of access and treatment (18.6%), healthcare capacity (11.5%), and care continuity amidst COVID-19 (7.4%). In contrast, reported concerns included issues around data security and privacy (17.5%), clinical uncertainty (17.0%), impact on patient-doctor relationship (11.9%), inequity in access and use (11.8%), misunderstanding health information (6.3%), and digital maturity (3.8%).Conclusions:Patients report many benefits with digital health services beyond immediate COVID-19 support, including improved access, timeliness, and enhanced healthcare capacity. Yet, some concerns remain, including some le
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Journal articleIqbal F, Joshi M, Davies G, et al., 2021,
Design of the pilot, proof of concept REMOTE-COVID trial: remote monitoring use in suspected cases of COVID-19 (SARS-CoV-2)
, Pilot and Feasibility Studies, Vol: 7, Pages: 1-7, ISSN: 2055-5784Background: The outbreak of SARS-CoV-2 (coronavirus, COVID-19), declared a pandemic by the World Health Organisation (WHO) is global health problem with ever-increasing attributed deaths. Vital sign trends are routinely used to monitor patients with changes in these parameters often preceding an adverse event. Wearable sensors can measure vital signs continuously (e.g. heart rate, respiratory rate, temperature) remotely and can be utilised to recognise early clinical deterioration. Methods: We describe the protocol for a pilot, proof-of-concept, observational study to be conducted in an engineered hotel near London airports, United Kingdom. The study is set to continue for the duration of the pandemic. Individuals arriving to London with mild symptoms suggestive of COVID-19 or returning from high risk areas requiring quarantine, as recommended by Public Health England, or healthcare professionals with symptoms suggestive of COVID-19 unable to isolate at home will be eligible for a wearable patch to be applied for the duration of their stay. Notifications will be generated should deterioration be detected through the sensor and displayed on a central monitoring hub viewed by nursing staff, allowing for trend deterioration to be noted. The primary objective is to determine the feasibility of remote monitoring systems in detecting clinical deterioration for quarantined individuals in a hotel. Discussion: This trial should prove the feasibility of a rapidly implemented model of healthcare delivery through remote monitoring during a global pandemic at a hotel, acting as an extension to a healthcare trust. Potential benefits would include reducing infection risk of COVID-19 to healthcare staff, with earlier recognition of clinical deterioration through ambulatory, continuous, remote monitoring using a discrete wearable sensor. We hope our results can power future, robust future randomised trials.
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